In this paper, a novel paradigm of mobile edgequantum computing (MEQC) is proposed, which brings quantum computing capacities to mobile edge networks that are closer to mobile users (i.e., edge devices). First, we pro...
In this paper, a novel paradigm of mobile edgequantum computing (MEQC) is proposed, which brings quantum computing capacities to mobile edge networks that are closer to mobile users (i.e., edge devices). First, we propose an MEQC system model where mobile users can offload computational tasks to scalable quantum computers via edge servers with cryogenic components and fault-tolerant schemes. Second, we show that it is NP-hard to obtain a centralized solution to the partial offloading problem in MEQC in terms of the optimal latency and energy cost of classical and quantum computing. Third, we propose a multi-agent hybrid discrete-continuous deep reinforcement learning using proximal policy optimization to learn the long-term sustainable offloading strategy without prior knowledge. Finally, experimental results demonstrate that the proposed algorithm can reduce at least 30% of the cost compared with the existing baseline solutions under different system settings.
Sixth generation(6G)enabled edge intelligence opens up a new era of Internet of everything and makes it possible to interconnect people-devices-cloud anytime,*** and more next-generation wireless network smart service...
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Sixth generation(6G)enabled edge intelligence opens up a new era of Internet of everything and makes it possible to interconnect people-devices-cloud anytime,*** and more next-generation wireless network smart service applications are changing our way of life and improving our quality of *** the hottest new form of next-generation Internet applications,Metaverse is striving to connect billions of users and create a shared world where virtual and reality ***,limited by resources,computing power,and sensory devices,Metaverse is still far from realizing its full vision of immersion,materialization,and *** this end,this survey aims to realize this vision through the organic integration of 6G-enabled edge artificial intelligence(AI)and ***,we first introduce three new types of edge-Metaverse architectures that use 6G-enabled edge AI to solve resource and computing constraints in *** we summarize technical challenges that these architectures face in Metaverse and the existing ***,we explore how the edge-Metaverse architecture technology helps Metaverse to interact and share digital ***,we discuss future research directions to realize the true vision of Metaverse with 6G-enabled edge AI.
Wireless communications are susceptible to eaves-dropping, and intelligent reflecting surface (IRS) as a relay capable of reconfiguring the propagation environment to extend the range of covert communication. In this ...
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ISBN:
(数字)9798350303582
ISBN:
(纸本)9798350303599
Wireless communications are susceptible to eaves-dropping, and intelligent reflecting surface (IRS) as a relay capable of reconfiguring the propagation environment to extend the range of covert communication. In this paper, we investigate the covert communication in which the ground transmitter secretly delivers information to the full-duplex receiver through a two-way IRS, avoiding detection by the warden. Furthermore, the error detection probability is determined with an optimal threshold at a warden, which is the worst case for covert transmission. We aim to maximize expected error detection probability of warden subject to the covertness constraint. To this end, we alternately optimize the prior probability and the transmit power of artificial noise while satisfying the outage probability and covertness requirement. Numerical results demonstrate the effectiveness of the proposed scheme for covert communications via the two-way IRS.
Analog circuit designautomation remains an intense area of attention and has seen both new and existing tools continued to be developed targeting different phases of the analog design flow to reduce development time ...
Analog circuit designautomation remains an intense area of attention and has seen both new and existing tools continued to be developed targeting different phases of the analog design flow to reduce development time and cost. One of the promising tools is the Berkeley analog generator (BAG2) framework which is an open-source analog layout generator for automating and verifying circuit layouts. It promises a process-independent flow as well as encourages design re-use due to using parameterized generators which can be scaled as required and this reduces the layout-development time compared to manual hand-made layouts. This work describes the effort and results of evaluating the BAG2 framework for the TSMC 65nm and Cadence GPDK 45nm processes. A case study is made with a number of circuits to discuss the problems in setting up and using BAG2 for the above technologies as well as the limitations and solutions required to utilize the framework effectively.
The popularity of Metaverse as an entertainment, social, and work platform has led to a great need for seamless avatar integration in the virtual world. In Metaverse, avatars must be updated and rendered to reflect us...
The popularity of Metaverse as an entertainment, social, and work platform has led to a great need for seamless avatar integration in the virtual world. In Metaverse, avatars must be updated and rendered to reflect users' behaviour. Achieving real-time synchronization between the virtual bilocation and the user is complex, placing high demands on the Metaverse Service Provider (MSP)'s rendering resource allocation scheme. To tackle this issue, we propose a semantic communication framework that leverages contest theory to model the interactions between users and MSPs and determine optimal resource allocation for each user. To reduce the consumption of network resources in wireless transmission, we use the semantic communication technique to reduce the amount of data to be transmitted. Under our simulation settings, the encoded semantic data only contains 51 bytes of skeleton coordinates instead of the image size of 8.243 megabytes. Moreover, we implement Deep Q-Network to optimize reward settings for maximum performance and efficient resource allocation. With the optimal reward setting, users are incentivized to select their respective suitable uploading frequency, reducing down-sampling loss due to rendering resource constraints by 66.076% compared with the traditional average distribution method. The framework provides a novel solution to resource allocation for avatar association in VR environments, ensuring a smooth and immersive experience for all users.
In the digital transformation era, Metaverse offers a fusion of virtual reality (VR), augmented reality (AR), and web technologies to create immersive digital experiences. However, the evolution of the Metaverse is sl...
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Web 3.0 is regarded as a revolutionary paradigm that enables users to securely manage data without a centralized authority. Blockchains, which enable data to be managed in a decentralized and transparent manner, are k...
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Artificial Intelligence Generated Content (AIGC) Services have significant potential in digital content creation. The distinctive abilities of AIGC, such as content generation based on minimal input, hold huge potenti...
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As an emerging technology, Digital Twin (DT) can provide a virtual presentation of the physical Intelligent Trans-portation systems (ITS) to enhance the applications of ITS such as cooperation perception. In cooperati...
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ISBN:
(数字)9798350387414
ISBN:
(纸本)9798350387421
As an emerging technology, Digital Twin (DT) can provide a virtual presentation of the physical Intelligent Trans-portation systems (ITS) to enhance the applications of ITS such as cooperation perception. In cooperative perception, accurate location is crucial for selecting proper cooperative vehicles (CoVs) to improve the perception performance. However, due to the high mobility of vehicles, the deviation between DT and physical world may lead to non-negligible location errors, which raises the challenges for achieving efficient CoV selection in cooperative perception. In this paper, we propose a DT-empowered multi-vehicle cooperative perception system, in which the CoV selection and bandwidth allocation are jointly optimized to improve the performance of cooperative perception. Specifically, an asyn-chronous federated learning scheme is deployed in DT for location prediction to mitigate the effect of the deviation. Based on the prediction results, the problem of joint predictive scheduling and bandwidth allocation is then formulated as the average delay minimization problem while reaching the required performances. The adaptive CoV selection and bandwidth allocation algorithm based on deep reinforcement learning is proposed to find the optimal scheduling strategy. Simulation results demonstrate that the proposed algorithm achieves the lowest average delay while effectively guaranteeing the performance requirement.
Web 3.0 is regarded as a revolutionary paradigm that enables users to securely manage data without a centralized authority. Blockchains, which enable data to be managed in a decentralized and transparent manner, are k...
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